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A multivariate model determined the odds ratio for each cancer associated with statin prescriptions adjusted for the potential confounding effects of variables listed above.
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Multivariate models determined that three covariates wearing gloves, acres treated, and repairing equipment were consistently predictive of exposure (Table 7).
AOR, 95% CI, and P values of the multivariate logistic-regression model determined by forward stepwise selection are shown in Table 5.
Table 3 presents the adjusted odds ratios, 95% confidence intervals, and p values of a multivariate logistic-regression model determined by stepwise selection.
The final multivariate model was determined once all of the predictors had been explored.
Once the final multivariate model was determined, the logistic model was converted to absolute risk using the method described in the Appendix.
Potential confounders were tested before selecting the final model by entering non-significant variables into the selected multivariate model and determined their effect on the odds ratios of the independent variables.
The order in which variables were introduced into the multivariate model was determined by the size of the p-value in the univariate analysis (starting with the smallest p-value).
The final multivariate model was determined using a backward elimination process in which terms that were not significant at a 2-sided 0.05 alpha level and not indicated to be confounding factors were dropped one-by-one until all factors were significant at a 2-sided 0.05 alpha level or acted as confounders.
Eight independent patient-, endoscopist- and endoscopy-related variables were analyzed by a multivariate model to determine their association with CP.
These variables were considered later in a multivariate model to determine their effects on study outcomes (Table 2).> -wrap-foot>> -wrap-foot> N, number; HIV, human immunodeficiency virus.
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